I’ve never been more excited for the future.
It seems like every day we hear of a new breakthrough in technology, medicine and robotics.
We are on the verge of a productivity boom like we haven’t seen in 100 years…
Since the advent of the car, electricity and the telephone.
Last Friday, we talked about how the AI economic boom is just getting started.
Because even if AI only boosts our productivity a little bit each year, the long-term effects will be enormous.
I wrote: Even a small acceleration — say, bumping productivity growth from 1.5% to 2.4% annually — could double economic output over two decades with the power of compounding.
And that’s still before taking into account AI’s ability to self-improve.
If AI starts helping us build better versions of itself — as we’re already seeing with tools like AutoGPT or open-source model tuning — then this compounding could accelerate even more.
That last section is in bold for a very good reason.
You see, it turns out the day before I wrote this, Google gave us a glimpse of what the self-improving future of AI might look like.
It was an announcement that came out without any fanfare. Just a blog post from the company introducing a new coding agent called AlphaEvolve.
But by all accounts, what Google just announced could be an absolute game-changer.
It might be the first self-improving AI.
And that means AI could dramatically improve from here.
In that case, productivity growth could accelerate at a pace humanity has never witnessed…
AI Evolves
AlphaEvolve is far more than just an AI agent that generates code…
It also creates algorithms.
Coding tells the computer what to do. But algorithms decide the smartest way to do it.
AlphaEvolve creates these algorithms, then it tests them, refines them and improves them.
This new agent is powered by Google’s most advanced language models, including Gemini Pro and Flash.
But it doesn’t rely on prompts the way something like ChatGPT does. Instead, it uses an evolutionary system that mimics natural selection.
That means good ideas survive and bad ones get discarded.
Over time, this helps the system get smarter. And by all accounts, AlphaEvolve has gotten exceptionally smart.
Over the last year, Google has been quietly deploying AlphaEvolve across its data centers, chip designs and AI training systems to boost efficiency.
And it’s finding better ways to solve some of the hardest problems in computer science.
Impressively, it discovered a faster method for multiplying matrices, a core operation in nearly every modern AI model. Mathematicians hadn’t been able to improve on this number for 56 years.
AlphaEvolve also proposed design changes to the chips that run Google’s AI infrastructure. Those suggestions are now being baked into the company’s next-gen TPUs, its custom accelerators for machine learning.
It’s even optimizing the actual code used to train large AI models, including the model powering AlphaEvolve.
In other words, we’re moving past AI merely helping humans build better tools.
AI is now helping itself evolve too.
And according to VentureBeat, this is helping Google save millions in computing costs.
But DeepMind didn’t stop there. It also fed AlphaEvolve dozens of open mathematical problems — the kind of puzzles that stump even world-class mathematicians.
And in 20% of cases, it came back with a better solution than anyone had found before.
Naturally, this is blowing people’s minds…
But I want to be clear that this doesn’t mean AI has developed intuition.
That’s not how this model works. It doesn’t have “aha” moments like a human would.
At least, not yet.
Instead, it simply tests idea after idea after idea… until it finds something that works better.
But this brute force approach is what makes the agent so powerful.
It doesn’t get tired. It doesn’t need weekends off. And it doesn’t forget what it learned last week.
It just keeps evolving.
As DeepMind CEO Demis Hassabis put it:
This is exactly what I was talking about last week.
If tools like AlphaEvolve become widespread — not just inside Google but across industries — they could transform everything from drug discovery to materials science to climate modeling.
And eventually, all that innovation loops back into the economy.
Smarter algorithms mean faster progress. Faster progress means better tools. Better tools mean more breakthroughs.
Each cycle spins the wheel a little faster…
Until the economic output of all this increased productivity really starts to compound.
AlphaEvolve could be our first glimpse into that future…
A future where we eventually reach artificial superintelligence.
Because it won’t just take smarter AI to get there.
It’ll take AI that makes itself smarter… faster than we can.
Regards,
Ian KingChief Strategist, Banyan Hill Publishing
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